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hbertv1-massive-intermediate_KD_new

This model is a fine-tuned version of gokuls/bert_12_layer_model_v1_complete_training_new_48 on the massive dataset. It achieves the following results on the evaluation set:

  • Loss: 1.6631
  • Accuracy: 0.8165

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 5e-05
  • train_batch_size: 64
  • eval_batch_size: 64
  • seed: 33
  • distributed_type: multi-GPU
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 50

Training results

Training Loss Epoch Step Validation Loss Accuracy
5.2865 1.0 180 4.1021 0.1692
4.1098 2.0 360 3.6293 0.2494
3.6635 3.0 540 3.1836 0.3665
3.311 4.0 720 2.9568 0.4555
3.0266 5.0 900 2.7684 0.4791
2.8087 6.0 1080 2.5803 0.5903
2.6276 7.0 1260 2.4481 0.6335
2.4728 8.0 1440 2.3491 0.6763
2.3497 9.0 1620 2.3474 0.6508
2.2557 10.0 1800 2.3618 0.6945
2.1673 11.0 1980 2.1769 0.7324
2.0929 12.0 2160 2.2181 0.7177
2.0125 13.0 2340 2.0942 0.7659
1.9507 14.0 2520 2.0009 0.7767
1.8811 15.0 2700 2.0316 0.7624
1.8356 16.0 2880 2.0107 0.7698
1.7935 17.0 3060 1.9687 0.7742
1.7436 18.0 3240 1.9601 0.7811
1.7158 19.0 3420 1.9357 0.7836
1.6848 20.0 3600 1.9413 0.7747
1.6421 21.0 3780 1.9428 0.7723
1.6091 22.0 3960 1.8787 0.7944
1.5758 23.0 4140 1.8953 0.7831
1.5557 24.0 4320 1.8503 0.7964
1.5249 25.0 4500 1.8481 0.7939
1.5082 26.0 4680 1.8342 0.7983
1.4827 27.0 4860 1.7922 0.7993
1.4552 28.0 5040 1.7805 0.7988
1.4296 29.0 5220 1.7730 0.7988
1.4067 30.0 5400 1.7724 0.7993
1.3843 31.0 5580 1.7438 0.8032
1.3721 32.0 5760 1.7842 0.7954
1.358 33.0 5940 1.7238 0.8087
1.3332 34.0 6120 1.6919 0.8091
1.3211 35.0 6300 1.7014 0.8042
1.3063 36.0 6480 1.6718 0.8131
1.2863 37.0 6660 1.6631 0.8165
1.2753 38.0 6840 1.6867 0.8091
1.2651 39.0 7020 1.6675 0.8067
1.2475 40.0 7200 1.6524 0.8072
1.2343 41.0 7380 1.6218 0.8165
1.2223 42.0 7560 1.6201 0.8155

Framework versions

  • Transformers 4.35.2
  • Pytorch 1.14.0a0+410ce96
  • Datasets 2.15.0
  • Tokenizers 0.15.0
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Evaluation results